avos <- read_csv("data/avocado.csv") %>%
clean_names()
New names:Rows: 18249 Columns: 14── Column specification ──────────────────────────────────────────────────────────────────────────────────────────
Delimiter: ","
chr (2): type, region
dbl (11): ...1, AveragePrice, Total Volume, 4046, 4225, 4770, Total Bags, Small Bags, Large Bags, XLarge Bags...
date (1): Date
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
avos %>%
skim()
── Data Summary ────────────────────────
Values
Name Piped data
Number of rows 18249
Number of columns 14
_______________________
Column type frequency:
character 2
Date 1
numeric 11
________________________
Group variables None
avos %>%
count(type)
avos %>%
ggplot(aes(x = average_price)) +
geom_histogram()
mod_alias <- lm(average_price ~ .,
data = avos)
mod_alias %>%
alias()
Model :
average_price ~ x1 + date + total_volume + x4046 + x4225 + x4770 +
total_bags + small_bags + large_bags + x_large_bags + type +
year + region
average_price looks a little right skewed, but not terribly, I think the normal distribution is acceptable
n_data <- nrow(avos)
# make a test index
test_index <- sample(1:n_data, size = n_data * 0.2)
# use test index to create test & training datasets
avos_test <- slice(avos, test_index)
avos_train <- slice(avos, -test_index)
avos_train_tidy <- avos_train %>%
mutate(season = case_when(
month(date) %in% c("3", "4", "5") ~ "spring",
month(date) %in% c("6", "7", "8") ~ "summer",
month(date) %in% c("9", "10", "11") ~ "autumn",
TRUE ~ "winter"),
is_organic = if_else(type == "organic", TRUE, FALSE),
year = as.factor(year),
proportion_x4046 = round(x4046 / total_volume * 100, 2),
proportion_x4225 = round(x4225 / total_volume * 100, 2),
proportion_x4770 = round(x4770 / total_volume * 100, 2),
proportion_other = round((total_volume - {x4770 + x4225 + x4046}) / total_volume * 100, 2)
) %>%
select(-c(x1, date, total_bags, type, region, x4046, x4225, x4770))
avos_train_tidy %>%
ggpairs()
Looks like the primary predictor could be is_organic, start here.
avo_model1_org <- lm(average_price ~ is_organic,
data = avos_train_tidy)
avo_model1_org %>%
summary()
Call:
lm(formula = average_price ~ is_organic, data = avos_train_tidy)
Residuals:
Min 1Q Median 3Q Max
-1.21297 -0.20297 -0.03007 0.18703 1.59703
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.160074 0.003680 315.25 <2e-16 ***
is_organicTRUE 0.492893 0.005215 94.52 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.315 on 14598 degrees of freedom
Multiple R-squared: 0.3797, Adjusted R-squared: 0.3796
F-statistic: 8935 on 1 and 14598 DF, p-value: < 2.2e-16
avo_model1_org %>%
autoplot()
Next best looks like it could be x4046, compare to ensure we have chosen the better primary
avo_model1_x4046 <- lm(average_price ~ proportion_x4046,
data = avos_train_tidy)
avo_model1_x4046 %>%
summary()
Call:
lm(formula = average_price ~ proportion_x4046, data = avos_train_tidy)
Residuals:
Min 1Q Median 3Q Max
-1.10976 -0.27688 -0.04555 0.22772 1.88576
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.5520116 0.0045485 341.22 <2e-16 ***
proportion_x4046 -0.0064384 0.0001467 -43.89 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.3784 on 14598 degrees of freedom
Multiple R-squared: 0.1166, Adjusted R-squared: 0.1165
F-statistic: 1926 on 1 and 14598 DF, p-value: < 2.2e-16
avo_model1_x4046 %>%
autoplot()
primary definitely confirmed to be is_organic, highest r2 by a large margin we’ll take that as our “champion”
Add the residuals from our chosen champion model and lets look at correlations again.
Not many good options, looks like the best options would be between proportion of x4225 or season or year
Start with proportion of x4225
avo_model2_x4225 <- lm(average_price ~ is_organic + proportion_x4225,
data = avos_train_tidy)
avo_model2_x4225 %>%
summary()
Call:
lm(formula = average_price ~ is_organic + proportion_x4225, data = avos_train_tidy)
Residuals:
Min 1Q Median 3Q Max
-1.11816 -0.19942 -0.02864 0.18456 1.62991
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.0154316 0.0053738 188.96 <2e-16 ***
is_organicTRUE 0.5141196 0.0050625 101.55 <2e-16 ***
proportion_x4225 0.0038614 0.0001082 35.67 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.3043 on 14597 degrees of freedom
Multiple R-squared: 0.4289, Adjusted R-squared: 0.4288
F-statistic: 5481 on 2 and 14597 DF, p-value: < 2.2e-16
avo_model2_x4225 %>%
autoplot()
Looking at season next
avo_model2_season <- lm(average_price ~ is_organic + season,
data = avos_train_tidy)
avo_model2_season %>%
summary()
Call:
lm(formula = average_price ~ is_organic + season, data = avos_train_tidy)
Residuals:
Min 1Q Median 3Q Max
-1.15803 -0.19896 -0.02216 0.18691 1.57197
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.290037 0.005782 223.110 <2e-16 ***
is_organicTRUE 0.495870 0.005018 98.817 <2e-16 ***
seasonspring -0.187878 0.007169 -26.206 <2e-16 ***
seasonsummer -0.071614 0.007382 -9.701 <2e-16 ***
seasonwinter -0.236946 0.007056 -33.581 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.3032 on 14595 degrees of freedom
Multiple R-squared: 0.4331, Adjusted R-squared: 0.4329
F-statistic: 2788 on 4 and 14595 DF, p-value: < 2.2e-16
avo_model2_season %>%
autoplot()
and finally year
avo_model2_year <- lm(average_price ~ is_organic + year,
data = avos_train_tidy)
avo_model2_year %>%
summary()
Call:
lm(formula = average_price ~ is_organic + year, data = avos_train_tidy)
Residuals:
Min 1Q Median 3Q Max
-1.32444 -0.18729 -0.01444 0.18556 1.65927
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.127290 0.005248 214.792 < 2e-16 ***
is_organicTRUE 0.496291 0.005103 97.260 < 2e-16 ***
year2016 -0.032848 0.006497 -5.056 4.34e-07 ***
year2017 0.140863 0.006477 21.749 < 2e-16 ***
year2018 -0.034974 0.010601 -3.299 0.000972 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.3083 on 14595 degrees of freedom
Multiple R-squared: 0.4138, Adjusted R-squared: 0.4137
F-statistic: 2576 on 4 and 14595 DF, p-value: < 2.2e-16
avo_model2_year %>%
autoplot()
season beats out the other two by having a higher r2, and a lower residual error
Lets add residuals and compare again
Looks like the next best would be year or proportion of x4225, our graphs are looking a little split up, so I feel we are missing something.
avo_model3_year <- lm(average_price ~ is_organic + season + year,
data = avos_train_tidy)
avo_model3_year %>%
summary()
Call:
lm(formula = average_price ~ is_organic + season + year, data = avos_train_tidy)
Residuals:
Min 1Q Median 3Q Max
-1.26308 -0.19025 -0.01173 0.17844 1.53338
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.252612 0.006642 188.598 < 2e-16 ***
is_organicTRUE 0.496372 0.004867 101.995 < 2e-16 ***
seasonspring -0.189362 0.007009 -27.017 < 2e-16 ***
seasonsummer -0.070884 0.007159 -9.901 < 2e-16 ***
seasonwinter -0.244534 0.007053 -34.671 < 2e-16 ***
year2016 -0.032363 0.006198 -5.221 1.80e-07 ***
year2017 0.143460 0.006180 23.214 < 2e-16 ***
year2018 0.066229 0.010501 6.307 2.93e-10 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.294 on 14592 degrees of freedom
Multiple R-squared: 0.4669, Adjusted R-squared: 0.4667
F-statistic: 1826 on 7 and 14592 DF, p-value: < 2.2e-16
avo_model3_year %>%
autoplot()
NA
NA
NA
Compare to prop of x4225
avo_model3_x4225 <- lm(average_price ~ is_organic + season + proportion_x4225,
data = avos_train_tidy)
avo_model3_x4225 %>%
summary()
Call:
lm(formula = average_price ~ is_organic + season + proportion_x4225,
data = avos_train_tidy)
Residuals:
Min 1Q Median 3Q Max
-1.06941 -0.19049 -0.01579 0.17540 1.68635
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.1486211 0.0067282 170.72 <2e-16 ***
is_organicTRUE 0.5140186 0.0048245 106.54 <2e-16 ***
seasonspring -0.1893819 0.0068568 -27.62 <2e-16 ***
seasonsummer -0.0743251 0.0070608 -10.53 <2e-16 ***
seasonwinter -0.2334913 0.0067490 -34.60 <2e-16 ***
proportion_x4225 0.0038075 0.0001032 36.90 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.2899 on 14594 degrees of freedom
Multiple R-squared: 0.4815, Adjusted R-squared: 0.4813
F-statistic: 2710 on 5 and 14594 DF, p-value: < 2.2e-16
avo_model3_x4225 %>%
autoplot()
prop x4225 looks good with some decent graphs and a higher r2 and lower residual standard error.
anova(avo_model3_x4225, avo_model2_season)
Analysis of Variance Table
Model 1: average_price ~ is_organic + season + proportion_x4225
Model 2: average_price ~ is_organic + season
Res.Df RSS Df Sum of Sq F Pr(>F)
1 14594 1245.1
2 14595 1362.8 -1 -117.75 1380.2 < 2.2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Looks like only maybe year could be useful here, but no others look particularly useful.
avo_model4_year <- lm(average_price ~ is_organic + season + proportion_x4225 + year,
data = avos_train_tidy)
avo_model4_year %>%
summary()
Call:
lm(formula = average_price ~ is_organic + season + proportion_x4225 +
year, data = avos_train_tidy)
Residuals:
Min 1Q Median 3Q Max
-1.17091 -0.17345 -0.01283 0.16620 1.58014
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.0615695 0.0075453 140.693 <2e-16 ***
is_organicTRUE 0.5177711 0.0045875 112.864 <2e-16 ***
seasonspring -0.1942966 0.0065720 -29.564 <2e-16 ***
seasonsummer -0.0740825 0.0067125 -11.036 <2e-16 ***
seasonwinter -0.2487260 0.0066130 -37.612 <2e-16 ***
proportion_x4225 0.0044979 0.0001003 44.834 <2e-16 ***
year2016 -0.0093886 0.0058336 -1.609 0.108
year2017 0.1925335 0.0058965 32.652 <2e-16 ***
year2018 0.1327397 0.0099564 13.332 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.2756 on 14591 degrees of freedom
Multiple R-squared: 0.5315, Adjusted R-squared: 0.5312
F-statistic: 2069 on 8 and 14591 DF, p-value: < 2.2e-16
avo_model4_year %>%
autoplot()
Seeing slight heteroskedasticity in the scale-location graph, and two layers in the Residuals vs Leverage graph, but a good line in Residuals vs fitted. Overall looks pretty good.
Lets add residuals and see if anything has improved.
Looks good, lets compare the model over both the train and test data
avos_test_tidy <- avos_test %>%
mutate(season = case_when(
month(date) %in% c("3", "4", "5") ~ "spring",
month(date) %in% c("6", "7", "8") ~ "summer",
month(date) %in% c("9", "10", "11") ~ "autumn",
TRUE ~ "winter"),
is_organic = if_else(type == "organic", TRUE, FALSE),
year = as.factor(year),
proportion_x4046 = round(x4046 / total_volume * 100, 2),
proportion_x4225 = round(x4225 / total_volume * 100, 2),
proportion_x4770 = round(x4770 / total_volume * 100, 2),
proportion_other = round((total_volume - {x4770 + x4225 + x4046}) / total_volume * 100, 2)
) %>%
select(-c(x1, date, total_bags, type, region, x4046, x4225, x4770))
train_model <- lm(average_price ~ is_organic + season + proportion_x4225 + year,
data = avos_train_tidy)
test_model <- lm(average_price ~ is_organic + season + proportion_x4225 + year,
data = avos_test_tidy)
train_model %>%
summary()
Call:
lm(formula = average_price ~ is_organic + season + proportion_x4225 +
year, data = avos_train_tidy)
Residuals:
Min 1Q Median 3Q Max
-1.17091 -0.17345 -0.01283 0.16620 1.58014
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.0615695 0.0075453 140.693 <2e-16 ***
is_organicTRUE 0.5177711 0.0045875 112.864 <2e-16 ***
seasonspring -0.1942966 0.0065720 -29.564 <2e-16 ***
seasonsummer -0.0740825 0.0067125 -11.036 <2e-16 ***
seasonwinter -0.2487260 0.0066130 -37.612 <2e-16 ***
proportion_x4225 0.0044979 0.0001003 44.834 <2e-16 ***
year2016 -0.0093886 0.0058336 -1.609 0.108
year2017 0.1925335 0.0058965 32.652 <2e-16 ***
year2018 0.1327397 0.0099564 13.332 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.2756 on 14591 degrees of freedom
Multiple R-squared: 0.5315, Adjusted R-squared: 0.5312
F-statistic: 2069 on 8 and 14591 DF, p-value: < 2.2e-16
test_model %>%
summary()
Call:
lm(formula = average_price ~ is_organic + season + proportion_x4225 +
year, data = avos_test_tidy)
Residuals:
Min 1Q Median 3Q Max
-1.08937 -0.16985 -0.00596 0.16503 1.22120
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.0708973 0.0154140 69.476 < 2e-16 ***
is_organicTRUE 0.5172642 0.0093157 55.526 < 2e-16 ***
seasonspring -0.1902042 0.0133691 -14.227 < 2e-16 ***
seasonsummer -0.0858974 0.0136445 -6.295 3.43e-10 ***
seasonwinter -0.2309263 0.0134299 -17.195 < 2e-16 ***
proportion_x4225 0.0042174 0.0001987 21.227 < 2e-16 ***
year2016 -0.0259408 0.0119034 -2.179 0.0294 *
year2017 0.1845227 0.0119083 15.495 < 2e-16 ***
year2018 0.1515200 0.0203088 7.461 1.07e-13 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.2792 on 3640 degrees of freedom
Multiple R-squared: 0.5212, Adjusted R-squared: 0.5201
F-statistic: 495.3 on 8 and 3640 DF, p-value: < 2.2e-16
train_model %>%
glance()
test_model %>%
glance()
NA
Well, looks like the model works (exceptionally) well on the test dataset, minor change in r2 and significant improvements in AIC and BIC, looks like we got lucky with our Test data.
avos_full_tidy <- avos %>%
mutate(season = case_when(
month(date) %in% c("3", "4", "5") ~ "spring",
month(date) %in% c("6", "7", "8") ~ "summer",
month(date) %in% c("9", "10", "11") ~ "autumn",
TRUE ~ "winter"),
is_organic = if_else(type == "organic", TRUE, FALSE),
year = as.factor(year),
proportion_x4046 = round(x4046 / total_volume * 100, 2),
proportion_x4225 = round(x4225 / total_volume * 100, 2),
proportion_x4770 = round(x4770 / total_volume * 100, 2),
proportion_other = round((total_volume - {x4770 + x4225 + x4046}) / total_volume * 100, 2)
) %>%
select(-c(x1, date, total_bags, type, region, x4046, x4225, x4770))
cv_10fold <- trainControl(method = "cv",
number = 10,
savePredictions = TRUE)
model_w_kfold <- train(average_price ~ is_organic + season + proportion_x4225 + year,
data = avos_full_tidy,
trControl = cv_10fold,
method = "lm")
model_w_kfold$pred
model_w_kfold$resample
mean(model_w_kfold$resample$RMSE)
[1] 0.2763769
mean(model_w_kfold$resample$Rsquared)
[1] 0.5288694
regsubsets_exhaustive <- regsubsets(average_price ~ ., data = avos_train_tidy, nvmax = 8, method = "exhaustive")
sum_regsubsets_exhaustive <- summary(regsubsets_exhaustive)
sum_regsubsets_exhaustive
Subset selection object
Call: regsubsets.formula(average_price ~ ., data = avos_train_tidy,
nvmax = 8, method = "exhaustive")
15 Variables (and intercept)
Forced in Forced out
total_volume FALSE FALSE
small_bags FALSE FALSE
large_bags FALSE FALSE
x_large_bags FALSE FALSE
year2016 FALSE FALSE
year2017 FALSE FALSE
year2018 FALSE FALSE
seasonspring FALSE FALSE
seasonsummer FALSE FALSE
seasonwinter FALSE FALSE
is_organicTRUE FALSE FALSE
proportion_x4046 FALSE FALSE
proportion_x4225 FALSE FALSE
proportion_x4770 FALSE FALSE
proportion_other FALSE FALSE
1 subsets of each size up to 8
Selection Algorithm: exhaustive
total_volume small_bags large_bags x_large_bags year2016 year2017 year2018 seasonspring seasonsummer
1 ( 1 ) " " " " " " " " " " " " " " " " " "
2 ( 1 ) " " " " " " " " " " " " " " " " " "
3 ( 1 ) " " " " " " " " " " "*" " " " " " "
4 ( 1 ) " " " " " " " " " " "*" " " " " " "
5 ( 1 ) " " " " " " " " " " "*" " " "*" " "
6 ( 1 ) " " " " " " " " " " "*" "*" "*" " "
7 ( 1 ) " " " " " " " " " " "*" "*" "*" " "
8 ( 1 ) " " " " " " " " " " "*" "*" "*" "*"
seasonwinter is_organicTRUE proportion_x4046 proportion_x4225 proportion_x4770 proportion_other
1 ( 1 ) " " "*" " " " " " " " "
2 ( 1 ) " " "*" " " "*" " " " "
3 ( 1 ) " " "*" " " "*" " " " "
4 ( 1 ) "*" "*" " " "*" " " " "
5 ( 1 ) "*" "*" " " "*" " " " "
6 ( 1 ) "*" "*" " " "*" " " " "
7 ( 1 ) "*" "*" "*" " " " " "*"
8 ( 1 ) "*" "*" "*" " " " " "*"
plot(regsubsets_exhaustive, scale = "adjr2")
plot(regsubsets_exhaustive, scale = "bic")
plot(sum_regsubsets_exhaustive$rsq, type = "b")
mod_noyear <- lm(average_price ~ . -year,
data = avos_train_tidy)
mod_w_year <- lm(average_price ~ .,
data = avos_train_tidy)
mod_noyear %>%
summary()
Call:
lm(formula = average_price ~ . - year, data = avos_train_tidy)
Residuals:
Min 1Q Median 3Q Max
-1.06955 -0.18784 -0.01558 0.17550 1.68925
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.552e+01 4.324e+01 0.590 0.554971
total_volume -2.276e-08 2.802e-09 -8.120 5.03e-16 ***
small_bags 9.949e-08 1.585e-08 6.276 3.57e-10 ***
large_bags -8.104e-08 2.277e-08 -3.559 0.000373 ***
x_large_bags 6.273e-07 2.352e-07 2.667 0.007658 **
seasonspring -1.894e-01 6.837e-03 -27.698 < 2e-16 ***
seasonsummer -7.697e-02 7.064e-03 -10.896 < 2e-16 ***
seasonwinter -2.329e-01 6.721e-03 -34.647 < 2e-16 ***
is_organicTRUE 5.076e-01 5.687e-03 89.268 < 2e-16 ***
proportion_x4046 -2.438e-01 4.324e-01 -0.564 0.572823
proportion_x4225 -2.399e-01 4.324e-01 -0.555 0.578947
proportion_x4770 -2.417e-01 4.324e-01 -0.559 0.576125
proportion_other -2.436e-01 4.324e-01 -0.564 0.573081
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.2886 on 14587 degrees of freedom
Multiple R-squared: 0.4867, Adjusted R-squared: 0.4862
F-statistic: 1152 on 12 and 14587 DF, p-value: < 2.2e-16
mod_w_year %>%
summary()
Call:
lm(formula = average_price ~ ., data = avos_train_tidy)
Residuals:
Min 1Q Median 3Q Max
-1.13245 -0.17377 -0.01277 0.16404 1.55831
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 7.728e+00 4.092e+01 0.189 0.850
total_volume -1.415e-08 2.673e-09 -5.295 1.21e-07 ***
small_bags 7.351e-08 1.504e-08 4.888 1.03e-06 ***
large_bags -1.190e-07 2.160e-08 -5.509 3.66e-08 ***
x_large_bags 2.514e-07 2.230e-07 1.127 0.260
year2016 8.308e-03 6.070e-03 1.369 0.171
year2017 2.195e-01 6.385e-03 34.372 < 2e-16 ***
year2018 1.636e-01 1.034e-02 15.831 < 2e-16 ***
seasonspring -1.991e-01 6.530e-03 -30.496 < 2e-16 ***
seasonsummer -8.001e-02 6.687e-03 -11.965 < 2e-16 ***
seasonwinter -2.511e-01 6.562e-03 -38.264 < 2e-16 ***
is_organicTRUE 5.458e-01 5.521e-03 98.856 < 2e-16 ***
proportion_x4046 -6.618e-02 4.092e-01 -0.162 0.872
proportion_x4225 -6.241e-02 4.092e-01 -0.152 0.879
proportion_x4770 -6.135e-02 4.092e-01 -0.150 0.881
proportion_other -6.752e-02 4.092e-01 -0.165 0.869
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.2731 on 14584 degrees of freedom
Multiple R-squared: 0.5402, Adjusted R-squared: 0.5398
F-statistic: 1142 on 15 and 14584 DF, p-value: < 2.2e-16
glmulti_fit <- glmulti(
average_price ~ .,
data = avos_full_tidy,
level = 2, # 2 = include pairwise interactions, 1 = main effects only (main effect = no pairwise interactions)
minsize = 0, # no min size of model
maxsize = -1, # -1 = no max size of model
marginality = TRUE, # marginality here means the same as 'strongly hierarchical' interactions, i.e. include pairwise interactions only if both predictors present in the model as main effects.
method = "g", # the problem is too large for exhaustive search, so search using a genetic algorithm
crit = bic, # criteria for model selection is BIC value (lower is better)
plotty = FALSE, # don't plot models as function runs
report = TRUE, # do produce reports as function runs
confsetsize = 10, # return best 100 solutions
fitfunction = lm # fit using the `lm` function
)
Initialization...
TASK: Genetic algorithm in the candidate set.
Initialization...
Algorithm started...
After 10 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+small_bags:total_volume+large_bags:small_bags+x_large_bags:small_bags+season:small_bags+season:large_bags+is_organic:total_volume+is_organic:small_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:large_bags+proportion_x4046:x_large_bags+proportion_x4046:season+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_other:total_volume+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+proportion_other:proportion_x4770+year:total_volume+year:season+year:proportion_x4225+year:proportion_other
Crit= 1526.33914481472
Mean crit= 1763.0713332705
Change in best IC: -8473.66085518528 / Change in mean IC: -8236.9286667295
After 20 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+season:x_large_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:season+proportion_x4046:x_large_bags+proportion_x4046:is_organic+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_other:total_volume+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+proportion_other:proportion_x4770+year:total_volume+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1364.78590523761
Mean crit= 1510.59893772864
Change in best IC: -161.553239577114 / Change in mean IC: -252.472395541855
After 30 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+small_bags:total_volume+large_bags:small_bags+x_large_bags:small_bags+season:x_large_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+proportion_other:proportion_x4770+year:total_volume+year:small_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1204.9271126019
Mean crit= 1331.48300680905
Change in best IC: -159.858792635707 / Change in mean IC: -179.115930919592
After 40 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+proportion_other:proportion_x4770+year:total_volume+year:small_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1168.1482173108
Mean crit= 1235.08513725988
Change in best IC: -36.7788952910998 / Change in mean IC: -96.3978695491728
After 50 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+proportion_other:proportion_x4770+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1137.50898935169
Mean crit= 1174.2094756892
Change in best IC: -30.639227959113 / Change in mean IC: -60.8756615706795
After 60 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+proportion_other:proportion_x4770+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1136.32136915807
Mean crit= 1162.04045186509
Change in best IC: -1.18762019361952 / Change in mean IC: -12.1690238241029
After 70 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+proportion_other:proportion_x4770+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1136.32136915807
Mean crit= 1162.04045186509
Change in best IC: 0 / Change in mean IC: 0
After 80 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+proportion_other:proportion_x4770+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1136.32136915807
Mean crit= 1149.87597822841
Change in best IC: 0 / Change in mean IC: -12.1644736366804
After 90 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1138.90390064502
Change in best IC: -8.39376742640366 / Change in mean IC: -10.9720775833948
After 100 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1137.00414602676
Change in best IC: 0 / Change in mean IC: -1.89975461825543
After 110 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1135.88769697415
Change in best IC: 0 / Change in mean IC: -1.11644905261073
After 120 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1135.88769697415
Change in best IC: 0 / Change in mean IC: 0
After 130 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1135.88769697415
Change in best IC: 0 / Change in mean IC: 0
After 140 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1135.88769697415
Change in best IC: 0 / Change in mean IC: 0
After 150 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1135.61839385366
Change in best IC: 0 / Change in mean IC: -0.269303120497625
After 160 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1135.36544254766
Change in best IC: 0 / Change in mean IC: -0.252951305990337
After 170 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1135.36544254766
Change in best IC: 0 / Change in mean IC: 0
After 180 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1135.36544254766
Change in best IC: 0 / Change in mean IC: 0
After 190 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1135.36544254766
Change in best IC: 0 / Change in mean IC: 0
After 200 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1135.23244510159
Change in best IC: 0 / Change in mean IC: -0.132997446070249
After 210 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1135.23244510159
Change in best IC: 0 / Change in mean IC: 0
After 220 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1135.23244510159
Change in best IC: 0 / Change in mean IC: 0
After 230 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1134.73976931801
Change in best IC: 0 / Change in mean IC: -0.49267578358581
After 240 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1134.73976931801
Change in best IC: 0 / Change in mean IC: 0
After 250 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1134.085412637
Change in best IC: 0 / Change in mean IC: -0.654356681010313
After 260 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1133.84663092128
Change in best IC: 0 / Change in mean IC: -0.238781715720734
After 270 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1133.84663092128
Change in best IC: 0 / Change in mean IC: 0
After 280 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1133.84663092128
Change in best IC: 0 / Change in mean IC: 0
After 290 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1133.84663092128
Change in best IC: 0 / Change in mean IC: 0
After 300 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1133.84663092128
Change in best IC: 0 / Change in mean IC: 0
After 310 generations:
Best model: average_price~1+year+total_volume+small_bags+large_bags+x_large_bags+season+is_organic+proportion_x4046+proportion_x4225+proportion_x4770+proportion_other+large_bags:small_bags+x_large_bags:small_bags+is_organic:total_volume+is_organic:small_bags+is_organic:large_bags+is_organic:x_large_bags+is_organic:season+proportion_x4046:total_volume+proportion_x4046:small_bags+proportion_x4046:x_large_bags+proportion_x4225:total_volume+proportion_x4225:large_bags+proportion_x4225:x_large_bags+proportion_x4225:is_organic+proportion_x4225:proportion_x4046+proportion_x4770:small_bags+proportion_x4770:is_organic+proportion_x4770:proportion_x4225+proportion_other:small_bags+proportion_other:large_bags+proportion_other:x_large_bags+proportion_other:season+proportion_other:is_organic+proportion_other:proportion_x4046+proportion_other:proportion_x4225+year:total_volume+year:small_bags+year:large_bags+year:season+year:is_organic+year:proportion_x4046+year:proportion_x4770+year:proportion_other
Crit= 1127.92760173167
Mean crit= 1133.84663092128
Improvements in best and average IC have bebingo en below the specified goals.
Algorithm is declared to have converged.
Completed.